Lim Yenkai, Fukuma Naoki, Totsika Makrina, Kenny Liz, Morrison Mark, Punyadeera Chamindie
The School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
Translational Research Institute, Brisbane, QLD, Australia.
Front Cell Infect Microbiol. 2018 Aug 3;8:267. doi: 10.3389/fcimb.2018.00267. eCollection 2018.
The oral microbiome can play a role in the instigation and progression of oral diseases that can manifest into other systemic conditions. These associations encourage the exploration of oral dysbiosis leading to the pathogenesis of cancers. In this study, oral rinse was used to characterize the oral microbiome fluctuation associated with oral cavity cancer (OCC) and oropharyngeal cancers (OPC). The study cohort consists of normal healthy controls ( = 10, between 20 and 30 years of age; = 10, above 50 years of age), high-risk individuals ( = 11, above 50 years of age with bad oral hygiene and/or oral diseases) and OCC and OPC patients ( = 31, HPV-positive; = 21, HPV-negative). Oral rinse samples were analyzed using 16S rRNA gene amplicon sequencing on the MiSeq platform. Kruskal-Wallis rank test was used to identify genera associated with OCC and OPC. A logistic regression analysis was carried out to determine the performance of these genera as a biomarker panel to predict OCC and OPC. In addition, a two-fold cross-validation with a bootstrap procedure was carried out in R to investigate how well the panel would perform in an emulated clinical scenario. Our data indicate that the oral microbiome is able to predict the presence of OCC and OPC with sensitivity and specificity of 100 and 90%, respectively. With further validation, the panel could potentially be implemented into clinical diagnostic and prognostic workflows for OCC and OPC.
口腔微生物群可在口腔疾病的引发和进展中发挥作用，这些口腔疾病可能会发展为其他全身性疾病。这些关联促使人们探索导致癌症发病机制的口腔生态失调。在本研究中，使用漱口水来表征与口腔癌（OCC）和口咽癌（OPC）相关的口腔微生物群波动情况。研究队列包括正常健康对照组（n = 10，年龄在20至30岁之间；n = 10，年龄在50岁以上）、高危个体（n = 11，年龄在50岁以上，口腔卫生差和/或患有口腔疾病）以及OCC和OPC患者（n = 31，HPV阳性；n = 21，HPV阴性）。使用MiSeq平台上的16S rRNA基因扩增子测序对漱口水样本进行分析。采用Kruskal-Wallis秩和检验来确定与OCC和OPC相关的菌属。进行逻辑回归分析以确定这些菌属作为预测OCC和OPC的生物标志物 panel 的性能。此外，在R中使用自举程序进行了两倍交叉验证，以研究该 panel 在模拟临床场景中的表现。我们的数据表明，口腔微生物群能够分别以100%的敏感性和90%的特异性预测OCC和OPC的存在。经过进一步验证，该 panel 可能会被应用于OCC和OPC的临床诊断和预后工作流程中。
